Finance & Artificial Intelligence | University of Twente · Bern Business School
Former roles in quantitative finance at Man Investments, Credit Suisse, Goldman Sachs, Bank of America Merrill Lynch
Research collaborations with ING, Deutsche Börse, European Central Bank, Bank for International Settlements, Quoniam Asset Management, and QCAM
Jörg Robert Osterrieder is Associate Professor of Finance and Artificial Intelligence at the University of Twente (Netherlands) and Professor of Finance at Bern Business School (Switzerland). His work focuses on the integration of artificial intelligence, machine learning, quantitative finance, risk management, and digital finance. He teaches and supervises students at the bachelor’s and master’s level, with particular emphasis on machine learning, reinforcement learning, and applications of AI in financial contexts.
Dr. Osterrieder coordinates the Marie Skłodowska-Curie Action Industrial Doctoral Network on Digital Finance, a €3.8 million EU-funded PhD training program that brings together more than 20 institutions and over 100 researchers. He is also Chair of the European COST Action on FinTech and AI in Finance (2020–2024), a collaborative network of 400 academics across 51 countries. In Switzerland, he serves as Principal Investigator for several research projects funded by the Swiss National Science Foundation, and contributes to the Steering Committee of the Luxembourg National Research Fund’s NCER Financial Technologies initiative.
In collaboration with financial institutions and regulatory bodies—including ING, the European Central Bank, the Bank for International Settlements, Deutsche Börse, Quoniam Asset Management, and QCAM Currency Asset Management—he works on topics such as AI-based portfolio optimization, credit risk modeling, and supervisory technology. Earlier in his career, he held quantitative and leadership positions at Man Investments, Credit Suisse Group, Goldman Sachs, and Merrill Lynch.
His academic work includes more than 25 peer-reviewed journal publications and numerous book chapters and conference proceedings. His research spans machine learning in finance, high-frequency trading, AI-based risk management, credit risk assessment, and the technological foundations of digital assets and blockchain. He is a regular speaker at international events, including the European Financial Regulation Conference, FinTech Days Tirana, and the Columbia-Bloomberg Machine Learning in Finance Conference.
Dr. Osterrieder holds editorial roles at several journals, including Frontiers in Artificial Intelligence in Finance, Frontiers in Financial Risk and Blockchain, Digital Finance (Springer), and the Journal of Investment Strategies. He has also served as guest editor for special issues on fintech, AI in finance, and cryptocurrencies, and actively reviews for journals in financial mathematics and quantitative finance.
He holds a Ph.D. in Mathematics from ETH Zürich, a Master’s in Mathematics from Syracuse University, and a Master’s in Business Economics from the University of Ulm. His work has been recognized with several awards, including the 2024 IETI Researcher Award, designation as a Top 20 European Quant & Finance Professor by Rebellion Research, and a Best Paper Award from the Journal of Risk and Financial Management. In 2016, he was a finalist for the Teaching Award at Zurich University of Applied Sciences.
He is a member of the Swiss Risk Association, Bachelier Finance Society, European Mathematical Society, European Finance Association, and American Finance Association. His work and commentary have appeared in international media outlets such as the Financial Times, The Sunday Times, SocietyBytes Science Magazine, Netzwoche Magazine, and Greater Zurich Area News.
For further details and publications, see Joerg Osterrieder’s profile or LinkedIn.
Prof. Dr. Joerg R. Osterrieder conducts applied research in collaboration with financial institutions, regulatory authorities, and technology partners. His work focuses on the application of artificial intelligence, machine learning, and quantitative methods in areas such as portfolio management, credit risk modeling, financial supervision, and digital finance.
He has been involved in projects with institutions including ING, the European Central Bank, the Bank for International Settlements, Deutsche Börse, Quoniam Asset Management, and QCAM Currency Asset Management. These collaborations have addressed model development, algorithmic trading, explainability in AI systems, and supervisory technology, among other topics.
In his academic roles, Prof. Osterrieder contributes to research initiatives that are designed to address both theoretical and practical challenges in financial markets. He participates in policy-related discussions and applied studies that support the development of data-driven tools in regulated financial environments.
Designed and implemented a systematic investment strategy based on risk-parity principles. The approach included volatility targeting, trend-following filters, and tail-risk overlays. Stress testing and signal robustness were key components. The strategy was deployed in live portfolio management.
Developed execution strategies for European equity markets, including VWAP, Implementation Shortfall, and participation-based models. This work involved extensive market microstructure analysis and transaction cost modeling. The strategies were implemented in a global execution platform used by institutional clients.
Contributed to the implementation of regulatory initiatives related to FATCA. Supported the rollout of internal processes across departments to align with evolving compliance requirements. The work focused on coordinating project tasks, documenting procedures, and ensuring alignment with regulatory timelines and standards.